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Communication Network at a Glance
Published in Vikas Kumar Jha, Bishwajeet Pandey, Ciro Rodriguez Rodriguez, Network Evolution and Applications, 2023
Vikas Kumar Jha, Bishwajeet Pandey, Ciro Rodriguez Rodriguez
The Internet Engineering Task Force (IETF) [10] is an open standards organization or a large open international community of the network designers, operators, vendors, and researchers concerned with the evolution of the Internet architecture and the smooth operation of the Internet. The IETF develops and promotes voluntary Internet standards and, in particular, the standards that comprise the Internet protocol suite (transmission control protocol/Internet protocol) with all of its participants and managers as volunteers; however, their work is usually funded by their employers or sponsors. It follows an open process so that any interested person can participate in the IETF work, can know what is being decided, and make the voice to be heard on the issue. The technical work of the IETF is done in its working groups, which are organized by topic into several areas including routing, transport, security, and so on. The IETF makes their documents, Working Group mailing lists, attendance lists, and the meeting minutes publicly available on the Internet. The IETF produces its documents for the technical competence needed and is also willing to listen to the technically competent input from any of the source to have the “engineering quality” in its design. The IETF makes the standards and also takes the ownership of all the aspects of a protocol standard based on the combined engineering judgment of its participants or volunteers and the real-world experience in implementing and deploying of those specifications.
Management’s Role
Published in Ray W. Wilson, Paul Harsin, Process Mastering, 2018
P. E. Ray W. Wilson, Paul Harsin
According to Horch, the technical aspects of creating and disseminating process masters is becoming a relatively straightforward matter of selecting a solution based on open Internet standards (such as e-mail, newsgroups, Web browsers, and servers). Computer networks based on Internet standards are now recognized as the most cost-effective approach throughout all levels of an organization. Building on Internet standards also gives great flexibility in selecting vendors and software packages, since any Internet standard by definition is designed to work with a large number of other systems.
Development of Standards, Codes, and Regulations
Published in Robert D. Hunter, for Engineers, 2017
Very importantly, the IETF fits itself into the complex standards world with extensive connections to the ITU and many other standards bodies. The Internet standards are freely available on the Web at www.ietf.org (accessed 12/7/10).
The General Attitudes towards Artificial Intelligence Scale (GAAIS): Confirmatory Validation and Associations with Personality, Corporate Distrust, and General Trust
Published in International Journal of Human–Computer Interaction, 2023
To assess the potential impact of computer expertise (as seen e.g., in Zhang & Dafoe, 2019), we asked participants to self-rate their computer expertise. None of the users in this sample chose “Hardly ever use the computer and do not feel very competent”; 1.3% rated themselves as “Slightly below average computer user, infrequently using the computer, using few applications”; 47% replied “Average computer user, using the internet, standard applications, etc.”; 36.8% chose “User of specialist applications but not an IT specialist”; 8.2% indicated “Considerable IT expertise short of full professional qualifications”; and 6.6% declared themselves to be “Professionally qualified computer scientist or IT specialist.” The wide diversity of occupations in our sample can be seen in the data file available via the Supplementary Materials.
Convolutional Neural Networks Hyperparameter Tunning for Classifying Firearms on Images
Published in Applied Artificial Intelligence, 2022
Isaac Cardoza, Juan P. García-Vázquez, Arnoldo Díaz-Ramírez, Verónica Quintero-Rosas
Another key aspect in constructing a highly accurate CNN-based classification model is the image data set employed. For an efficient handgun image classification model, it is important to consider not only images of static weapons but also scenarios of real-life where those firearms were being held by humans in different threatening stances. That is why, looking for a balance between consistency and production environment usefulness, we decided to form our own data set using only some images from other existent data sets. For instance, we included the Internet standard ”Gun-Detection” data set Annamraju (2019), from which we took 3,000 images for the true class. Then, we added 2,973 more images from Roboflow.com “Object-Detection/Pistols” data set Webpage (2020). And once collected, the data set was verified image by the image taking care to not include any image with watermarks, video game or animated images, toy guns, photo filters, thick frames, or any other kind of visual disturbance to keep it as clean and useful as possible. During this curating process, more than 50% of the images collected were discarded. As a consequence, to reach the desired quantity of images for the true class (3,000), we filled the rest with the results of the istockphoto.com images database using the search query ”gun pointed” iSstock webpage (2021). As for the false class, we needed a variety of scenes to provide the model with the ability to generalize the background. Also, we needed large quantities of pictures of people holding different kinds of objects to make sure that the model would not learn that people were the main feature for the true class, but guns. Under that criterion, we selected approximately 2,400 images from the Microsoft Common objects in context (COCO) data set Lin et al. (2014), whereas the rest were obtained while doing manual searches in Google Images. Examples of the contents of both classes within our data set can be observed in Figure 3.